Engineering at the Speed of Thought: Accelerating Processes with Multi-Agent AI and Synera

Imagine a scenario familiar to many organizations: A customer request arrives requiring input from multiple departments. Instead of quick, coordinated action, the request lingers in shared inboxes, moving slowly between specialists, accumulating delays. By the time a response is ready, inefficiencies are glaringly evident. This challenge is common across industries, from automotive engineering RFQs to healthcare protocol evaluations.

Synera, a process automation company, tackles this problem head-on, especially in engineering. Their vision is clear: liberate engineers from manual, repetitive tasks, allowing them to focus on creativity and problem-solving. In partnership with AWS, Synera has developed a prototype multi-agent system to streamline complex engineering processes.

Multi-Agent AI Systems: A Revolutionary Approach

Multi-agent AI systems represent a breakthrough in artificial intelligence. Instead of relying on a single AI model, these systems deploy multiple specialized agents that work together, much like human experts in a team. Each agent brings unique expertise to the task and communicates with other agents through structured protocols.

The advantage of multi-agent systems lies in their ability to perform asynchronous tasks, handle complex workflows, and scale by adding new agents when needed. This makes them particularly suitable for engineering contexts where cross-disciplinary collaboration is essential.

Synera’s Approach: Leveraging Multi-Agent AI

Synera’s vision for engineering process automation revolves around combining AI agents with existing engineering tools. Their platform enables engineers to model workflows visually, integrate CAx tools, and publish these workflows as callable APIs. By making these automated workflows accessible through APIs, engineers can build complex automation without needing deep programming knowledge.

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In collaboration with AWS, Synera developed a multi-agent system for processing RFQs (Requests for Quotations) in engineering. The system uses Amazon Bedrock for AI inference, which ensures performance and data security, essential in protecting intellectual property during complex analysis.

Multi-Agent System Architecture

The RFQ system built by Synera and AWS follows a hybrid architecture that combines supervisor and network elements. The core of the system is the RFQ Manager Agent, which orchestrates the flow of tasks among specialized agents:

• Commodity Analysis Agent: Analyzes specifications to optimize configurations.
• CAD Analysis Agent: Validates geometry and calculates volumes.
• Assembly Analysis Agent: Recommends manufacturing approaches.
• Purchasing Analysis Agent: Evaluates supplier availability and lead times.
• Costing Analysis Agent: Calculates unit and total costs.

The manager agent dynamically routes tasks, either passing them directly between agents or overseeing the entire process. This adaptability ensures efficiency while maintaining coordination across specialized functions.

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Real-World Impact: Speed and Efficiency

Traditionally, RFQ processing in engineering can take weeks, involving multiple engineers and stages. The multi-agent system reduced this process to mere minutes while maintaining accuracy and consistency. The business implications are significant:

• Faster customer responses lead to higher win rates.
• Consistent quality regardless of team member availability.
• Simultaneous handling of multiple RFQs.
• Reduced manual errors and enhanced innovation focus for engineers.

Transforming Engineering Workflows

Synera’s platform not only automates routine analysis but also democratizes access to specialized knowledge. Engineers design workflows, which AI agents then execute, freeing up human experts to focus on strategic decision-making. As AI systems become more advanced, engineers can transition to roles that emphasize creativity, problem-solving, and innovation.

Conclusion

By integrating multi-agent AI systems with Synera’s process automation tools, engineering teams can transform their workflows, responding to complex tasks in minutes rather than weeks. The result is a dynamic, efficient, and innovative engineering environment that keeps human creativity at the forefront. As industries adapt to this new paradigm, organizations leveraging multi-agent systems will gain a competitive edge, accelerating their engineering processes while maintaining high-quality standards.

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About Amazon Web Services (AWS)

Amazon Web Services (AWS), launched in 2006, offers reliable, scalable, low-cost cloud infrastructure, transforming capital expenses into variable costs. Businesses benefit from Amazon's expertise, accessing resources on demand, reducing costs, and accelerating results. AWS powers hundreds of thousands of businesses globally, with data centers in the U.S., Europe, Singapore, and Japan.
Website AWS

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More information about AWS & Synera, can be found in our current press release: https://www.synera.io/press/synera-joins-the-aws-partner-network